Markdown Cheat Sheet

The markdown RStudio cheat sheat is here. Various information can be found here, including shortcuts to modify the text. Bootstrap typography codes also seem to be available to format markdown HTML documents; this feature has not been thoroughly tested by the author.

Referencing

Referencing important previous work and the scientific principles that underpin research is a vital aspect of any report. The default bibliography list that is used by this template is found in assets/bib/bibliography.bib. The author has included these references in the document for illustrative purposes (2017); however, they have nothing to do with anything that is written here (R Core Team 2021; Spinu, Grolemund, and Wickham 2021).

Bibliographic information for R packages are automatically generated (and loaded) with LoadandCite (Gandrud 2016). By default, the package bibliography is stored in assets/bib/packages.bib, which is overwritten on each Knit and should not be manually altered.

References are automatically placed at the end of the document, so it is important that a header, such as # References, is placed at the end of your markdown document.

broom::tidy()

The broom::tidy() (Robinson, Hayes, and Couch 2021) function may be used to convert the output into a data frame that is compatible with kable When data is supplied from a model, which may be more appropraite for a report or publication.

For example, the summary output of a linear model looks like:

model <- lm(Sepal.Length ~ Sepal.Width + Petal.Width, data = iris)

summary(model)

Call:
lm(formula = Sepal.Length ~ Sepal.Width + Petal.Width, data = iris)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.2076 -0.2288 -0.0450  0.2266  1.1810 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  3.45733    0.30919   11.18  < 2e-16 ***
Sepal.Width  0.39907    0.09111    4.38 2.24e-05 ***
Petal.Width  0.97213    0.05210   18.66  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.4511 on 147 degrees of freedom
Multiple R-squared:  0.7072,    Adjusted R-squared:  0.7033 
F-statistic: 177.6 on 2 and 147 DF,  p-value: < 2.2e-16

Broom defines tidying methods for extracting three kinds of statistics from an object (see here):

• tidy(): component-level statistics
• glance(): model-level statistics
• augment(): observation-level statistics

tidy():

glance():

augment():

jtools

Two of the functions in the jtools (Long 2021) package are useful to produce tables and figures of model output.

models <- lapply(c("setosa", "versicolor", "virginica"),
                 function(x) lm(Sepal.Length ~ Sepal.Width + Petal.Width, data = iris, subset = Species == x))
names(models) <- c("setosa", "versicolor", "virginica")

jtools::export_summs(models,
                     error_format = "CI [{conf.low}, {conf.high}]",
                     exp = FALSE)

do.call(jtools::plot_summs,
        c(unname(models),
          list(model.names = names(models),
               exp = FALSE,
               colors = unname(telethonkids_cols()[c(2, 4, 8)])))) + 
  labs(title = "Example of plot_summs", subtitle = "Input is a list of models")

These will work for many different types of models.

Colour schemes

There are three colour schemes built into this theme: scale_colour_telethonkids(light), scale_colour_telethonkids(dark) and scale_colour_telethonkids(grey). These colour themes are implemented by adding the appropriate theme to the ggplot code:

ggplot(iris, aes(Petal.Width, Petal.Length, color = Species)) +
  labs(title = "Iris Dataset", x = "Petal Width", y = "Petal Length") +
  geom_point(size = 4) +
  scale_color_telethonkids("light") +
  theme_classic()

A continuous colour theme can be implemented by adding the argument discrete = FALSE the scale_colour_telethonkids():

ggplot(iris, aes(Petal.Width, Petal.Length, color = Petal.Length)) +
  geom_point(size = 4, alpha = .6) +
  scale_color_telethonkids(discrete = FALSE, palette = "dark") +
  theme_classic()

Bar plots can also be ‘filled’ by discrete variables with differnt palettes by using scale_fill_telethonkids(palette = mixed, guide = none).

To ensure the image is responsive on different sized screens, the code out.extra = figure should be included in the R chunk options (this calls an option hook defined in assets/R/hooks.R).